Creative professionals often utilize a variety of images as part of content creation, such as to generate marketing materials, backgrounds, illustrate books, presentations, and so forth. For instance, creative professionals may create images themselves which are then included in the content, such as for part of a presentation, and may also obtain images from outside sources, such as from a content sharing service. Accordingly, even a single item of content may include a variety of images obtained from a variety of different sources.
In some instances, these images include text, such as text on a road sign, a person's shirt, a logo, and so forth. Text, and the fonts used to render the text in the image, are one of the top elements of design. Accordingly, recognition of a font used to render text within an image and also to find similar fonts (e.g., to promote a similar look and feel to an item of content) is an important factor in creation of content that is visually pleasing to users. Conventional techniques to do so, however, typically rely on manual user interaction on the part of the creative professional, which may introduce errors due to reliance on the manual dexterity of the user that performs this interaction. Although automated techniques have been developed, these are often also prone to error, resource intensive, and inefficient and thus limited to devices having sufficient processing resources to perform these conventional techniques.